AWS Machine Learning Blog

ML model explainability with Amazon SageMaker Clarify and the SKLearn pre-built container

Amazon SageMaker Clarify is a new machine learning (ML) feature that enables ML developers and data scientists to detect possible bias in their data and ML models and explain model predictions. It’s part of Amazon SageMaker, an end-to-end platform to build, train, and deploy your ML models. Clarify was made available at AWS re:Invent 2020. […]

Build accurate ML training datasets using point-in-time queries with Amazon SageMaker Feature Store and Apache Spark

This post is co-written with Raphey Holmes, Software Engineering Manager, and Jason Mackay, Principal Software Development Engineer, at GoDaddy. GoDaddy is the world’s largest services platform for entrepreneurs around the globe, empowering their worldwide community of over 20 million customers—and entrepreneurs everywhere—by giving them all the help and tools they need to grow online. GoDaddy […]

Create a large-scale video driving dataset with detailed attributes using Amazon SageMaker Ground Truth

Do you ever wonder what goes behind bringing various levels of autonomy to vehicles? What the vehicle sees (perception) and how the vehicle predicts the actions of different agents in the scene (behavior prediction) are the first two steps in autonomous systems. In order for these steps to be successful, large-scale driving datasets are key. […]

Improve newspaper digitalization efficacy with a generic document segmentation tool using Amazon Textract

We are living in a digital age. Information that used to be spread by printouts is disseminated at unforeseen speeds through digital formats. In parallel to the inventions of new types of media, an increasing number of archives and libraries are trying to create digital repositories with new technologies. Digitization allows for preservation by creating […]

Build XGBoost models with Amazon Redshift ML

Amazon Redshift ML allows data analysts, developers, and data scientists to train machine learning (ML) models using SQL. In previous posts, we demonstrated how customers can use the automatic model training capability of Amazon Redshift to train their classification and regression models. Redshift ML provides several capabilities for data scientists. It allows you to create […]

Automate Amazon SageMaker Studio setup using AWS CDK

Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). Studio provides a single web-based visual interface where you can perform all ML development steps required to prepare data, as well as build, train, and deploy models. You can quickly upload data, create new notebooks, train and tune models, move […]

Connect to your Amazon CloudWatch data to detect anomalies and diagnose their root cause using Amazon Lookout for Metrics

This post was reviewed and updated May 2022, to include the option of continuous detector mode. Amazon Lookout for Metrics uses machine learning (ML) to automatically detect and diagnose anomalies (outliers from the norm) without requiring any prior ML experience. Amazon CloudWatch provides you with actionable insights to monitor your applications, respond to system-wide performance changes, […]

Event-based fraud detection with direct customer calls using Amazon Connect

Several recent surveys show that more than 80% of consumers prefer spending with a credit card over cash. Thanks to advances in AI and machine learning (ML), credit card fraud can be detected quickly, which makes credit cards one of the safest and easiest payment methods to use. The challenge with cards, however, is that […]

Build patient outcome prediction applications using Amazon HealthLake and Amazon SageMaker

Healthcare data can be challenging to work with and AWS customers have been looking for solutions to solve certain business challenges with the help of data and machine learning (ML) techniques. Some of the data is structured, such as birthday, gender, and marital status, but most of the data is unstructured, such as diagnosis codes […]

Build multi-class classification models with Amazon Redshift ML

November 2022: Post was reviewed and updated to announce support of Prediction Probabilities for Classification problems  using Amazon Redshift ML. Amazon Redshift ML simplifies the use of machine learning (ML) by using simple SQL statements to create and train ML models from data in Amazon Redshift. You can use Amazon Redshift ML to solve binary classification, multi-class […]